When loads acting on joint implants are measured with instrumented implants, they vary much in time, intra- as well as inter-individually. Nevertheless, the users of such data need “typical” load-time patterns, for example for testing or analytically improving joint implants. Simply calculating an arithmetic mean curve delivers untypical results (see figure, blue line). The averaging software “averDTW” calculates an average signal from several varying, time dependent signals, using a dynamic time warping procedure (see figure, red line).
k signals are first time-normalized and then time-distorted (warped) so that the summed squared distance between all of them become a minimum. All distorted signals are treated statistically, obtaining different output signals: arithmetic mean, minimum, maximum:
and median, 25 percentiles, 75 percentiles:
For detail see:
Bender A., Bergmann G., Determination of Typical Patterns from Strongly Varying Signals,Comput Methods Biomech Biomed Engin. 2012;15(7):761-9.
averDTW_vb2015.zip – contains demo program, demo data, dll library, and source code of demo program, written in Visual Basic 2019 [2.6 MB, MD5 Checksum: 01E2CC323E812E8C1D3E694745D5133C or md5 check file ]